Abstract

Bayesian models provide a principled way to deal with uncertainty. In cognitive tasks the uncertainty is mainly in how to represent the observed data, as there is usually not enough data to uniquely determine the representation. Bayesian models of cognition implement a general method for dealing with representational uncertainty which can be applied to explain human performance in various cognitive tasks.